Prediction

Model

fofr/replicate-tshirt:cbd108aa

crzbsxdb4bclefyjnylbmqk3ii

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

19.9s

Created

almost 2 years ago

Webhook

–

Input

prompt: a mystical forest, black background, svg, design
negative_prompt: text, words, cropped
control_illusion_strength: 1.35
number_of_images: 2

{
  "control_illusion_strength": 1.35,
  "negative_prompt": "text, words, cropped",
  "number_of_images": 2,
  "prompt": "a mystical forest, black background, svg, design"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_9WH**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/replicate-tshirt using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/replicate-tshirt:cbd108aa8d25f65873969b6ce626c9f7c60187882bdc9f8ea210380d1e1f7da7",
  {
    input: {
      control_illusion_strength: 1.35,
      negative_prompt: "text, words, cropped",
      number_of_images: 2,
      prompt: "a mystical forest, black background, svg, design"
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_9WH**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run fofr/replicate-tshirt using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/replicate-tshirt:cbd108aa8d25f65873969b6ce626c9f7c60187882bdc9f8ea210380d1e1f7da7",
    input={
        "control_illusion_strength": 1.35,
        "negative_prompt": "text, words, cropped",
        "number_of_images": 2,
        "prompt": "a mystical forest, black background, svg, design"
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_9WH**********************************

This is your API token. Keep it to yourself.

Run fofr/replicate-tshirt using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "fofr/replicate-tshirt:cbd108aa8d25f65873969b6ce626c9f7c60187882bdc9f8ea210380d1e1f7da7",
    "input": {
      "control_illusion_strength": 1.35,
      "negative_prompt": "text, words, cropped",
      "number_of_images": 2,
      "prompt": "a mystical forest, black background, svg, design"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "id": "crzbsxdb4bclefyjnylbmqk3ii",
  "model": "fofr/replicate-tshirt",
  "version": "cbd108aa8d25f65873969b6ce626c9f7c60187882bdc9f8ea210380d1e1f7da7",
  "input": {
    "control_illusion_strength": 1.35,
    "negative_prompt": "text, words, cropped",
    "number_of_images": 2,
    "prompt": "a mystical forest, black background, svg, design"
  },
  "logs": "Random seed set to: 3156845569\nChecking inputs\n✅ /tmp/inputs/replicate-logo.png\n====================================\nRunning workflow\ngot prompt\nExecuting node 69, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode\nExecuting node 66, title: Apply ControlNet, class type: ControlNetApply\nExecuting node 2, title: KSampler (Efficient), class type: KSampler (Efficient)\nRequested to load ControlNet\nLoading 1 new model\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:14,  1.31it/s]\n 10%|█         | 2/20 [00:01<00:13,  1.30it/s]\n 15%|█▌        | 3/20 [00:02<00:12,  1.31it/s]\n 20%|██        | 4/20 [00:03<00:12,  1.32it/s]\n 25%|██▌       | 5/20 [00:03<00:11,  1.33it/s]\n 30%|███       | 6/20 [00:04<00:10,  1.32it/s]\n 35%|███▌      | 7/20 [00:05<00:09,  1.33it/s]\n 40%|████      | 8/20 [00:06<00:08,  1.33it/s]\n 45%|████▌     | 9/20 [00:06<00:08,  1.34it/s]\n 50%|█████     | 10/20 [00:07<00:07,  1.34it/s]\n 55%|█████▌    | 11/20 [00:08<00:06,  1.35it/s]\n 60%|██████    | 12/20 [00:08<00:05,  1.35it/s]\n 65%|██████▌   | 13/20 [00:09<00:05,  1.35it/s]\n 70%|███████   | 14/20 [00:10<00:04,  1.33it/s]\n 75%|███████▌  | 15/20 [00:11<00:03,  1.33it/s]\n 80%|████████  | 16/20 [00:12<00:03,  1.33it/s]\n 85%|████████▌ | 17/20 [00:12<00:02,  1.34it/s]\n 90%|█████████ | 18/20 [00:13<00:01,  1.35it/s]\n 95%|█████████▌| 19/20 [00:14<00:00,  1.39it/s]\n100%|██████████| 20/20 [00:14<00:00,  1.41it/s]\n100%|██████████| 20/20 [00:14<00:00,  1.35it/s]\nExecuting node 6, title: Save Image, class type: SaveImage\nPrompt executed in 16.73 seconds\noutputs:  {'2': {'images': []}, '6': {'images': [{'filename': 'tshirt_00001_.png', 'subfolder': '', 'type': 'output'}, {'filename': 'tshirt_00002_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nContents of /tmp/outputs:\ntshirt_00001_.png\ntshirt_00002_.png\n[Path('/tmp/outputs/tshirt_00001_.png'), Path('/tmp/outputs/tshirt_00002_.png')]",
  "output": [
    "https://replicate.delivery/pbxt/3hofPHovWL36banK0H4rq50PiUtnZjBpN5HdM4ZGfkyNNggSA/tshirt_00001_.png",
    "https://replicate.delivery/pbxt/He9grTqSSn26VCTHSZeOxn1dXyiiDFZBJyMHxjB9HWHPNggSA/tshirt_00002_.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-03-15T13:46:35.779775Z",
  "started_at": "2024-03-15T13:46:35.821473Z",
  "completed_at": "2024-03-15T13:46:55.624534Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/crzbsxdb4bclefyjnylbmqk3ii/cancel",
    "get": "https://api.replicate.com/v1/predictions/crzbsxdb4bclefyjnylbmqk3ii"
  },
  "metrics": {
    "predict_time": 19.803061,
    "total_time": 19.844759
  }
}

Generated in

19.8 seconds

Tweak it Report

Random seed set to: 3156845569 Checking inputs ✅ /tmp/inputs/replicate-logo.png ==================================== Running workflow got prompt Executing node 69, title: CLIP Text Encode (Prompt), class type: CLIPTextEncode Executing node 66, title: Apply ControlNet, class type: ControlNetApply Executing node 2, title: KSampler (Efficient), class type: KSampler (Efficient) Requested to load ControlNet Loading 1 new model 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:14, 1.31it/s] 10%|█ | 2/20 [00:01<00:13, 1.30it/s] 15%|█▌ | 3/20 [00:02<00:12, 1.31it/s] 20%|██ | 4/20 [00:03<00:12, 1.32it/s] 25%|██▌ | 5/20 [00:03<00:11, 1.33it/s] 30%|███ | 6/20 [00:04<00:10, 1.32it/s] 35%|███▌ | 7/20 [00:05<00:09, 1.33it/s] 40%|████ | 8/20 [00:06<00:08, 1.33it/s] 45%|████▌ | 9/20 [00:06<00:08, 1.34it/s] 50%|█████ | 10/20 [00:07<00:07, 1.34it/s] 55%|█████▌ | 11/20 [00:08<00:06, 1.35it/s] 60%|██████ | 12/20 [00:08<00:05, 1.35it/s] 65%|██████▌ | 13/20 [00:09<00:05, 1.35it/s] 70%|███████ | 14/20 [00:10<00:04, 1.33it/s] 75%|███████▌ | 15/20 [00:11<00:03, 1.33it/s] 80%|████████ | 16/20 [00:12<00:03, 1.33it/s] 85%|████████▌ | 17/20 [00:12<00:02, 1.34it/s] 90%|█████████ | 18/20 [00:13<00:01, 1.35it/s] 95%|█████████▌| 19/20 [00:14<00:00, 1.39it/s] 100%|██████████| 20/20 [00:14<00:00, 1.41it/s] 100%|██████████| 20/20 [00:14<00:00, 1.35it/s] Executing node 6, title: Save Image, class type: SaveImage Prompt executed in 16.73 seconds outputs: {'2': {'images': []}, '6': {'images': [{'filename': 'tshirt_00001_.png', 'subfolder': '', 'type': 'output'}, {'filename': 'tshirt_00002_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== Contents of /tmp/outputs: tshirt_00001_.png tshirt_00002_.png [Path('/tmp/outputs/tshirt_00001_.png'), Path('/tmp/outputs/tshirt_00002_.png')]